1. Field of the Invention
The present invention is directed in general to magnetic resonance tomography as employed in medicine for examining patients. The present invention is specifically directed to a method for magnetic resonance imaging as well as to a magnetic resonance tomography apparatus for the implementation of this method, wherein an interactive contrast optimization is implemented.
2. Description of the Prior Art
MRT is based on the physical phenomenon of nuclear magnetic resonance and has been successfully utilized as an imaging method in medicine and biophysics for more than 15 years. In this examination method, the subject is exposed to a strong, constant magnetic field. As a result, the nuclear spins of the atoms in the subject align, the spins having been previously irregularly oriented. Radio-frequency energy can then excite these “ordered” nuclear spins to a specific oscillation. This oscillation generates the actual measured signal in MRT, which is picked up with suitable reception coils. The measurement subject can be spatially encoded in all three spatial directions by utilizing non-homogeneous magnetic fields generated by gradient coils. A free selection of the slice to be imaged is possible, so that tomograms of the human body can be registered in all directions. In medical diagnostics, MRT is particularly distinguished as a tomographic imaging method as being a “non-invasive” examination with a versatile contrast capability. Due to the excellent presentation of soft tissue, MRT has developed into a method that is often superior to X-ray computer tomography (CT).
One of the principal advantages of MR tomography is the excellent ability to display of soft tissue, i.e. an excellent soft part contrast in the reconstructed MRT images. The reason for this is the different relaxation times T1 (of the longitudinal magnetization) and T2 (of the transverse magnetization) as well as T2* (effective relaxation time of the transverse magnetization) of the tissue that reflect the interaction of the hydrogen nuclei with their environment in a complex way. However, the proton densities p also play a certain part in the MRT imaging. The term “proton density” means that part of the tissue protons whose magnetic resonance signal contributes to the MR image signal. These are essentially the water protons and the methyl protons of the mobile fatty acids. Hydrogen nuclei in cell membranes, proteins or in other relatively rigid macromolecules generally do not contribute to the MRT signal; their signal usually already has decayed to zero at the point in time of the data acquisition.
Whereas the image contrast of a CT image is dependent only on the electron density of the observed tissue, the magnetic resonance signal, and thus the character of the MRT image, is determined by the three tissue-specific parameters ρ, T1, T2 and T2* as well as by the type of pulse sequence employed and the corresponding exposure parameters. This variability of the MRT signal offers the possibility of optimizing the image contrast between specific tissue structures with a suitable selection of the pulse sequence and the exposure parameters. In this way, there is the possibility of achieving an optimally good differentiation between specific tissue structures—for example, healthy tissue and tumor tissue.
According to the prior art, for example in clinical practice, MRT images are being acquired with different exposure parameters that are selected such that the image contrast of the individual images is mainly determined by a single tissue parameter. Images of this type are made in this context of T1, T2, T2* or ρ weighted images.
FIG. 3 shows such a method according to the prior art. In step S8, a specific imaging sequence is selected (for example, T1, T2, or ρ weighted) and the determination of the parameters characterizing the sequence (for example, repetition time TR, echo time TE, flip angle a, etc. are determined). The measurement subsequently ensues in step S9, the raw data of the measured slice according to step S10 being generated therewith. The raw data, which are present in the form of a matrix, are processed in a computer in step S11 (including Fourier transformation) and are presented to the user as MRT image according to step S12—usually at a picture screen. In step S13, the user must then make a decision as to whether the contrast of the image satisfies the requirements for the diagnosis (step S14). A sub-optimum contrast of the image can be accepted according to step S19. If the contrast of the image is inadequate, the measurement according to step S16 is repeated with other parameters, possibly with a different sequence type as well (begin again with step S8), until an image having adequate quality in terms of the contrast has been generated.
A disadvantage of this known method is that it is dependent on the resulting contrast weighting of the selected sequence and no targeted contrast improvement is possible. Additionally, this type of contrast optimization is decidedly time-consuming since all of the above-recited steps must be repeated as warranted.